There has been increasing focus on reducing the environmental impact of many products due to ever increasing concerns over the detrimental effects on human health and on the environment. One way to measure the environmental impact of a product is to evaluate the environmental impact through an approach known as life-cycle assessment (LCA), which considers a product across its entire life-cycle from extraction of raw materials, through manufacturing processes, transportation, operation, and end of life recycling. Conventional LCA methods use numerous input and output variables. The input variables often include hundreds, if not thousands of materials, processes, and related data, such as, mass and energy consumption. The output variables often include one or more environmental impact metrics, such as, greenhouse gas emissions, resource consumption, toxicity, and health damage.
Often, given a particular LCA, it is not intuitive to a product designer as to how the product attributes (input variables) are to be modified to reduce the environmental impact of a product (output variables). As such, designers are currently required to iteratively attempt multiple configurations for the products and to re-run the LCA on the multiple configurations to evaluate whether the iterated design has successfully reduced the environmental impact of the product. This is often a time consuming and laborious process for the designer because of the large number of possible input variables, and often may not lead to a feasible solution even after multiple iterations are performed.
In other instances, product designers have attempted generic design optimization and techniques, which include approaches for multi-objective design. These objectives may broadly be categorized as DfX (Design for X), where X may for example refer to the environment, recycling, or manufacturing. In most of these instances, the product designer is required to manually expend additional time and resources, which is often significant. Moreover, DfX requires specialized expertise and is therefore difficult to implement in general-purpose product design tools.